The financial industry continues to rely to a very great extent on paper documents, such as checks, drafts and deposit tickets. These documents continue to increase in number, and accordingly must be processed in larger and larger numbers. Since a finite amount of time for document processing remains, the physical resources which must be devoted to processing must, in the absence of increases in efficiency, be increased.
In order to increase the efficiency of document processing, it is desirable to automate the process as much as possible. Typically, routing information is pre-imprinted onto a financial document in magnetic ink, but the amount of the document is not encoded by the time it is presented to a financial institution. Typically, this information must be manually imprinted onto the document, a process which is slower than the rest of the processing operation, and which typically requires a human operator to read the amount and then key it in. Other information typically appears on the document but it is not normally encoded onto the document in standard machine-readable form. This information includes, for example, the name of the payee, and the signature of the drawer. Automated recognition of this information can be extremely useful in combating fraud and forgery, and for providing additional checkpoints for the prevention of errors.
Automated document recognition technologies presently exist, but presently existing technologies are slower than the rest of the document processing operation. In the case of financial documents, automated document recognition can be very difficult, as documents vary widely. Documents can be of any of a number of sizes, for example. Moreover, the needed information can appear on the document in a number of forms, for example, computer-printed in any of a large number of fonts, typewritten, or handwritten in one of myriad different writing styles. Technologies now exist to analyze many of these writing and printing styles, but analysis often requires an appreciable length of time when compared with the time needed to physically move the documents.
Modern document processing equipment typically transports and processes machine-encoded documents at a very high speed, so that a typical transport system would send the document to the next stage before analysis could be completed. Automated recognition technology could be accommodated by the slowing of the transport system, but this would decrease the efficiency and the document-handling capacity of the entire system. In effect, converting a high speed document transport to a medium or low speed transport.
Thus, it would be highly advantageous to provide a system for buffering documents so that additional time could be devoted to document recognition for individual documents without adversely affecting the speed of the rest of the system. By way of example, where an additional percentage of documents can be recognized by automated recognition technology, these documents can be machine-encoded bypassing manual encoding by human operators and resulting in substantial savings in time and money. It would further be advantageous to provide a redundant document recognition system, permitting continued operation of the recognition system in the event of a partial breakdown.